×

RIONA

swMATH ID: 30227
Software Authors: Góra, Grzegorz; Wojna, Arkadiusz
Description: RIONA: A new classification system combining rule induction and instance-based learning. The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decision is predicted not on the basis of the whole support set of all rules matching a test case, but the support set restricted to a neighbourhood of a test case. The size of the optimal neighbourhood is automatically induced during the learning phase. The empirical study shows the interesting fact that it is enough to consider a small neighbourhood to achieve classification accuracy comparable to an algorithm considering the whole learning set. The combination of (k)-NN and a rule-based algorithm results in a significant acceleration of the algorithm using all minimal rules. Moreover, the presented classifier has high accuracy for both kinds of domains: more suitable for (k)-NN classifiers and more suitable for rule based classifiers.
Homepage: https://pdfs.semanticscholar.org/ba97/561e8e74da507f0bb310fb3159c49d2f5cae.pdf
Keywords: rule induction; nearest neighbour method; instance-based learning
Related Software: Rseslib; LERS; ROSETTA; C4.5; RSES; DIXER; ElemStatLearn; WEKA; RoughSets; Guerry; itsmr; ENDER; BRENT; TwitterRank; NetKit; SLIQ; daTac; RSBR_; ROSECON; RRIA
Cited in: 9 Documents

Citations by Year